Portrait of Junha Yoo

Junha Yoo

junha.yoo@mila.quebec
Master's Research - McGill University
Supervisor
Derek Nowrouzezahrai
Co-supervisor
James Richard Forbes
Research Topics
Autonomous Robotics Navigation
Computer Vision
Robotics

Publications

DIVO: Continuous-time DVL-Inertial-Visual Odometry for Unmanned Underwater Vehicles
Kyungmin Jung
Angad Bajwa
Junha Yoo
Arturo Del Castillo Bernal
James Richard Forbes
This paper presents a novel acoustic-visual-inertial odometry solution leveraging a continuous-time trajectory estimation framework for unma… (see more)nned underwater vehicles. Underwater environments present unique challenges for visual localization and mapping, such as light attenuation, illumination variance, and the presence of particulate matter. This motivates the use of additional sensing modalities and a visual tracking pipeline that is robust to diverse subsea conditions. The proposed system is the first continuous-time trajectory estimation framework based on Gaussian processes to fuse asynchronous measurements from a Doppler velocity log, a stereo camera, and an inertial measurement unit. Additionally, a novel visual frontend is proposed, incorporating learning-based feature extraction and matching that is robust to the specific challenges that subsea environments present. The proposed framework enables seamless integration of additional sensor modalities in continuous-time and is adaptable to different environments without reconfiguration. The proposed system is extensively tested on real-world underwater inspection datasets, where it outperforms state-of-the-art visual-inertial and acoustic-visual-inertial SLAM algorithms in accuracy, robustness, and trajectory coverage. Notably, the proposed system outperforms the state-of-the-art despite only forming short-term visual data associations.
2026-07-05
arXiv (preprint)
doi.org
arxiv.org